Eliminate manual analysis and discover actionable intelligence more quickly

August 21, 2018

When the chances of solving a case drop by half after the first 48 hours, investigative teams need to work fast. Collaboration, speed and accuracy are essential. Case backlogs, processing times and time consuming analysis of digital device, drone, cloud and computer data in large, static PDF reports put investigations at risk. To successfully solve cases and keep communities safe, teams need solutions to move beyond siloed data repositories and manual analysis to transform the intelligence gathering process.

Spotlight

Starburst

Starburst is the data analytics engine for all of your information. It offers the most efficient and effective analytics engine for your database system, data lake, or data mesh. The company unlocks the value of dispersed data by making its access quick and straightforward, regardless of where it resides. Starburst searches data across any database, enabling data-driven enterprises to take immediate action. With Starburst, teams can reduce the overall cost of their infrastructure and analytics expenditures, avoid vendor lock-in, and use the business's current tools. Starburst, used by Apache Corporation, Doordash, Comcast, FINRA, Priceline, and VMware, enables enterprises to make smarter, more rapid choices on all data.

OTHER WHITEPAPERS
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The Evolution of Data 3.0

whitePaper | October 17, 2022

Today, massive amounts of data are collected, processed, and stored for a range of analytical purposes around the world. Every customer, device, transaction, email, and image leaves a data trail. At present, this data is growing too big, changing too fast, and becoming hyper distributed. The traditional ways of doing integration and analytics are no longer viable or scalable. It is not feasible to create millions of data pipelines and to continue moving large amounts of raw data to a data lake or a centralized data warehouse.

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Build a thriving business using data and analytics at scale

whitePaper | February 7, 2020

The problem is that growing volumes of data can lead to data paralysis, because no one knows quite where to begin or how to use it. Siloed information sources, no data management strategy, disconnected spreadsheets or analytical tools and poor data quality all work to compound the issues you’re facing.

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Enhancing Data Empowerment in Financial Services with Modern Cloud Analytics

whitePaper | November 30, 2022

Modern cloud analytics can help financial services organisations to gain greater insight into their ever-increasing volumes of data, enabling them to improve customer experience, boost productivity and generate new revenue streams.

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Customization of Access Control in Microsoft Azure

whitePaper | December 6, 2022

Datamatics provides intelligent solutions for data-driven businesses to increase productivity and enhance the customer experience. With a complete digital approach, Datamatics portfolio spans across Information Technology Services, Business Process Management, Engineering Services and Big Data & Analytics all powered by Artificial Intelligence

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Manual Replication of MySQL Database Using MySQL Workbench

whitePaper | December 19, 2022

When an Azure region is not available due to issues at the Datacenter level, this should not affect the availability of data. Hence, database replication is required to avoid data loss at any given point in time. Some Microsoft Azure regions do not support Azure database replication in different regions. (Refer to the image given below) To overcome this, manual replication of MySQL database using MySQL workbench is the only feasible option.

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6 best practices for cloud data integration

whitePaper | September 1, 2022

Organizations often adopt a hybrid cloud strategy when deploying their first analytical solution to the cloud. The cloud combines sheer infinite scalability with consumption-based pricing. These are desirable attributes for analytical environments that require scalability and can be very expensive when scaled for maximum capacity over an extended period.

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Spotlight

Starburst

Starburst is the data analytics engine for all of your information. It offers the most efficient and effective analytics engine for your database system, data lake, or data mesh. The company unlocks the value of dispersed data by making its access quick and straightforward, regardless of where it resides. Starburst searches data across any database, enabling data-driven enterprises to take immediate action. With Starburst, teams can reduce the overall cost of their infrastructure and analytics expenditures, avoid vendor lock-in, and use the business's current tools. Starburst, used by Apache Corporation, Doordash, Comcast, FINRA, Priceline, and VMware, enables enterprises to make smarter, more rapid choices on all data.

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